Abstract
In this paper we describe the evaluation of three machine learning algorithms that assign ontology based answer types to questions in a question-answering task. We used shallow and syntactical features to classify about 1400 German questions with a Decision Tree, a k-nearest Neighbor, and a Naïve Bayes algorithm.
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Davidescu, A., Heyl, A., Kazalski, S., Cramer, I., Klakow, D. (2007). Classifying German Questions According to Ontology-Based Answer Types. In: Decker, R., Lenz, H.J. (eds) Advances in Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70981-7_69
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DOI: https://doi.org/10.1007/978-3-540-70981-7_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70980-0
Online ISBN: 978-3-540-70981-7
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